Sampling complete

# Sampling complete - Stat 250 Gunderson Lecture Notes...

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23 Stat 250 Gunderson Lecture Notes Chapter 3: Sampling: Surveys and How to Ask Questions Do not put faith in what statistics say until you have carefully considered what they do not say. -- William W. Watt So far we have mainly studied how to summarize data - exploratory data analysis - with graphs and numbers. The knowledge of how the data were generated is one of the key ingredients for translating data intelligently. Chapters 3 and 4 focus on how to collect useful data. Chapter 3 focuses on how to conduct surveys, how to make sure they are representative, and what can go wrong. We will highlight some ideas here. We will not go in to detail on the various sampling methods in Sections 3.3 and 3.4, but will comment on random sampling. The sampling ideas in Chapter 3 overall make sense and there are a number of good examples. And there will be a few questions from this chapter on the homework and exams. 3.1 Collecting and Using Sample Data Wisely There are two main types of statistical techniques that can be applied to data. Definitions: Descriptive Statistics: Describing data using numerical summaries (such as the mean, IQR, etc.) and graphical summaries (such as histograms, bar charts, etc.). Inferential Statistics: Using sample information to make conclusions about a larger group of items/individuals than just those in the sample. In most statistical studies, the objective is to use a small group of units (the sample) to make an inference (a decision or judgment) about a larger group (the population). Definitions: Population : The entire group of items/individuals that we want information about, about which inferences are to be made. Sample : The smaller group, the part of the population we actually examine in order to gather information. Variable : The characteristic of the items or individuals that we want to learn about. One way to view these terms is through a Basket Model : Population= basket of balls, 1 ball for each unit in population. X = variable (value of variable is recorded on each ball as small x ) Sample = a few balls selected from the basket.

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24 Fundamental Rule for Using Data for Inference: Available data can be used to make inferences about a much larger group if the data can be considered to be representative with regard to the question(s) of interest. One principal way to guarantee that sample data represents a larger population is to use a (simple) random sample. Try It! Exercise 3.15 page 107 For each situation explain whether or not the Fundamental Rule holds. c. Research Question: Does a majority of adults in state support lowering the drinking age to 19? Available Data: Opinions on whether or not the legal drinking age should be lowered to 19 years old, collected from a random sample of 1000 adults in the state. Yes, a “random sample” was taken of a reasonably large size from the population of interest …
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## This note was uploaded on 12/31/2011 for the course STATS 250 taught by Professor Gunderson during the Winter '10 term at University of Michigan.

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Sampling complete - Stat 250 Gunderson Lecture Notes...

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